Leadership simulations have been in use for years. Typically, leadership simulations are comprised of (1) books or periodicals which analyze organizational issues and offer advice regarding leadership and management interventions and likely outcomes, (2) generic computer modeling tools (such as spreadsheets), (3) graphical representation tools, (4) optimization analytics and system dynamic models to be used to model specific problems identified and codified by the user, (5) decision support tools which can be used to quantify the economic impact of various alternative approaches, (6) simulations of fictitious or composite firms used to offer virtual experiences similar to experiences likely to occur in actual organizations, and (7) role playing environments in which humans interact with each other and the environment in controlled situations, whether real, artificial or imagined, for the purpose of gaining leadership experience and learning leadership skills.
A problem with conventional leadership simulations is that they do not simulate the underlying non-linear dynamics of organizations in a way that exposes the realistic impact leadership, or management activity patterns and behaviors might have on short term performance and long term sustainability. Another problem with conventional leadership simulations is that they focus on the behaviors an individual might exercise as a leader of people, and not on the impacts the individual has on organizational processes and dynamics. Another problem with conventional leadership simulations is that they focus on individual decisions or problems to be solved, when the nature of organizations is that many actions and decisions are interconnected. This leads to what is called the ‘law of unintended consequences’: in an organizational context any action triggers many other events, many of which are unforeseen. In addition, dynamic systems such as organizations settle around attractor states and operate within an attractor basin of a complex system. Because of this, individual acts or decisions are small perturbations to the system which, in order to maintain operation in a state of dynamic equilibrium or stability, are dampened by the organizations balancing feedback loops. This implies that single decisions, if enacted in isolation, trigger counteracting actions which serve to dampen the initial effect. This organization leveling effect has been referred to as “policy resistance” because it is often observed empirically as countermeasures which serve to dampen the effects of policy intervention (See, Sterman, J. D. (2000), Business Dynamics: Systems thinking and modeling for a complex world, McGraw-Hill). Another problem with the above-referenced approaches is that they are limited to human-run organizations (e.g., for-profit and non-profit corporations, partnerships, etc.), and do not contemplate non-human organizations (such as computer systems), and leadership of computerized agents.
While the above-referenced solutions may be suitable for the particular purpose to which they address, they are not as suitable for individuals in leader and/or manager roles to be able to model their organization as a system and to simulate a plurality of actions that might be taken and their impact on the non-linear dynamics of the organization, its functions, capabilities, processes and outcomes. Additionally, the above solutions cannot be used to dynamically control complex computerized environments, where autonomous computerized agents must be organized and led.
Thus, there is presently a need for a system and method which enables individuals (or computerized agents) in leader and/or manager roles to be able to model their organization as a system and to simulate a plurality of actions that might be taken and their impact on the non-linear dynamics of the organization, its functions, capabilities, processes and outcomes.